Connect from your IDE

This page summarizes features of developer tools that enable you to connect to Databricks from your IDE.

Compare IDE tools

The following table compares tools for connecting to Databricks from your IDE.

Tool	Use cases
SSH tunnel	Connect your local IDE to classic, serverless, or serverless GPU compute over SSH. Run code in the same environment as your cluster or serverless compute.
IDE extension	Connect Visual Studio Code or Cursor to a Databricks workspace with a few clicks. Define, deploy, and run Declarative Automation Bundles from your IDE. Run local Python files on Databricks compute, or run files and notebooks as Lakeflow Jobs.
Databricks Connect	Connect any IDE, notebook server, or custom application to Databricks compute. Write code with Spark APIs and run it remotely on Databricks compute instead of a local Spark session.

Tool	Use cases
SSH tunnel	Connect your local IDE to classic, serverless, or serverless GPU compute over SSH. Run code in the same environment as your cluster or serverless compute.
IDE extension	Connect Visual Studio Code or Cursor to a Databricks workspace with a few clicks. Define, deploy, and run Declarative Automation Bundles from your IDE. Run local Python files on Databricks compute, or run files and notebooks as Lakeflow Jobs.
Databricks Connect	Connect any IDE, notebook server, or custom application to Databricks compute. Write code with Spark APIs and run it remotely on Databricks compute instead of a local Spark session.